ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1909.03585
  4. Cited By
Learning to Sample: an Active Learning Framework

Learning to Sample: an Active Learning Framework

9 September 2019
Jingyu Shao
Qing Wang
Fangbing Liu
ArXiv (abs)PDFHTML

Papers citing "Learning to Sample: an Active Learning Framework"

15 / 15 papers shown
Title
Towards Comparable Active Learning
Towards Comparable Active Learning
Thorben Werner
Johannes Burchert
Lars Schmidt-Thieme
156
0
0
24 Feb 2025
A Survey on Deep Active Learning: Recent Advances and New Frontiers
A Survey on Deep Active Learning: Recent Advances and New Frontiers
Dongyuan Li
Zhen Wang
Yankai Chen
Xue Liu
Weiping Ding
Manabu Okumura
165
31
0
01 May 2024
Importance of negative sampling in weak label learning
Importance of negative sampling in weak label learning
Ankit Parag Shah
Fuyu Tang
Zelin Ye
Rita Singh
Bhiksha Raj
42
0
0
23 Sep 2023
Hazards in Deep Learning Testing: Prevalence, Impact and Recommendations
Hazards in Deep Learning Testing: Prevalence, Impact and Recommendations
Salah Ghamizi
Maxime Cordy
Yuejun Guo
Mike Papadakis
And Yves Le Traon
35
1
0
11 Sep 2023
How To Overcome Confirmation Bias in Semi-Supervised Image
  Classification By Active Learning
How To Overcome Confirmation Bias in Semi-Supervised Image Classification By Active Learning
Sandra Gilhuber
Rasmus Hvingelby
Mang Ling Ada Fok
Thomas Seidl
63
1
0
16 Aug 2023
Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection
Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection
Erik Arakelyan
Arnav Arora
Isabelle Augenstein
56
10
0
01 Jun 2023
Algorithm Selection for Deep Active Learning with Imbalanced Datasets
Algorithm Selection for Deep Active Learning with Imbalanced Datasets
Jifan Zhang
Shuai Shao
Saurabh Verma
Robert D. Nowak
112
21
0
14 Feb 2023
Does Configuration Encoding Matter in Learning Software Performance? An
  Empirical Study on Encoding Schemes
Does Configuration Encoding Matter in Learning Software Performance? An Empirical Study on Encoding Schemes
Jing Gong
Tao Chen
61
14
0
30 Mar 2022
Reinforced Meta Active Learning
Reinforced Meta Active Learning
Michael Katz
Eli Kravchik
OffRL
58
1
0
09 Mar 2022
Addressing practical challenges in Active Learning via a hybrid query
  strategy
Addressing practical challenges in Active Learning via a hybrid query strategy
D. Agarwal
Pravesh Srivastava
Sergio Martin del Campo
Balasubramaniam Natarajan
Babji Srinivasan
49
7
0
07 Oct 2021
Accountable Error Characterization
Accountable Error Characterization
Amita Misra
Zhe Liu
J. Mahmud
27
0
0
10 May 2021
ErGAN: Generative Adversarial Networks for Entity Resolution
ErGAN: Generative Adversarial Networks for Entity Resolution
Jingyu Shao
Qing Wang
Asiri Wijesinghe
Erhard Rahm
GAN
36
8
0
18 Dec 2020
Learning active learning at the crossroads? evaluation and discussion
Learning active learning at the crossroads? evaluation and discussion
L. Desreumaux
V. Lemaire
77
12
0
16 Dec 2020
Ask-n-Learn: Active Learning via Reliable Gradient Representations for
  Image Classification
Ask-n-Learn: Active Learning via Reliable Gradient Representations for Image Classification
Bindya Venkatesh
Jayaraman J. Thiagarajan
18
4
0
30 Sep 2020
Importance of Self-Consistency in Active Learning for Semantic
  Segmentation
Importance of Self-Consistency in Active Learning for Semantic Segmentation
S. Golestaneh
Kris Kitani
SSL
54
36
0
04 Aug 2020
1